Prompt-Matched Semantic Segmentation. (arXiv:2208.10159v2 [cs.CV] UPDATED)

The objective of this work is to explore how to effectively and efficiently
adapt pre-trained visual foundation models to downstream tasks, e.g., image
semantic segmentation. Conventional methods usually fine-tuned the entire
networks for each specific dataset, which will be burdensome to store massive
parameters of these networks. Several recent works attempted to insert some
extra trainable parameters into the frozen networks to learn visual prompts for
parameter-efficient tuning. However, these works showed poor generality as they
were designed specifically for …

arxiv segmentation semantic